Plot
EDA Plot for each crop data
# Plotting the Value over Years for a specific Item, loop for all items
# change y aixs as unit is different for each Element Value
for (item in unique(data_fao$Item)) {
plot <- ggplot(data = data_fao %>% filter(Item == item), aes(x = Year, y = Value, color = Element)) +
geom_line() +
labs(title = paste("Trends Over Time for", item), x = "Year", y = "Value")
#print(plot)
# Plotting the Value over Years for each Element (e.g., "Apples")
options(repr.plot.width = 35, repr.plot.height = 8) # Adjust width and height
facet_plot <- ggplot(data = data_fao %>% filter(Item == item), aes(x = Year, y = Value)) +
geom_line() +
facet_wrap(~ Element, scales = "free_y") +
labs(title = paste("Trends Over Time for", item), x = "Year", y = "Value") +
theme_minimal()+
scale_x_continuous(breaks = seq(min(data_fao$Year), max(data_fao$Year), by = 3))+
theme(axis.text.x = element_text(angle = 90, hjust = 1, vjust = 0.5)) # Rotate x-axis labels
# Change 'by' to your preferred interval
print(facet_plot)
}
## [1] "Adding columns for year and week"
## # A tibble: 6,609 × 5
## # Groups: Year [127]
## Year Week week_Mean_Temperature week_Mean_Percentile_95 week_Mean_EHF_95
## <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1899 9 0.925 6.03 NaN
## 2 1899 10 4.59 6.82 NaN
## 3 1899 11 1.86 7.38 NaN
## 4 1899 12 1.87 8.71 NaN
## 5 1899 13 3.91 10.1 -8.19
## 6 1899 14 5.99 11.1 -14.3
## 7 1899 15 6.26 12.0 -13.2
## 8 1899 16 8.11 13.4 -14.1
## 9 1899 17 7.77 14.3 -10.2
## 10 1899 18 7.53 15.4 -13.0
## # ℹ 6,599 more rows
linear reg for yield VS EHF 95
Abbotsford
## [1] "There are 47 NA in the matrix X in Abbotsford station"
## [1] "Results for crop: Apples"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -57270 -10358 2532 12719 50521
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 344369.8 89677.0 3.840 0.00495 **
## Week_9 -3993.2 10247.8 -0.390 0.70695
## Week_10 321.9 5583.2 0.058 0.95544
## Week_11 -389.8 8027.6 -0.049 0.96246
## Week_12 -580.3 6797.0 -0.085 0.93406
## Week_13 -9676.1 10926.5 -0.886 0.40169
## Week_14 7807.3 8638.4 0.904 0.39250
## Week_15 8572.3 7632.7 1.123 0.29397
## Week_16 2343.9 6596.7 0.355 0.73154
## Week_17 -5542.3 9669.5 -0.573 0.58228
## Week_18 996.9 6208.4 0.161 0.87642
## Week_19 7751.4 4517.8 1.716 0.12455
## Week_20 2900.8 7820.3 0.371 0.72032
## Week_21 2987.8 6425.2 0.465 0.65432
## Week_22 -1442.2 5387.7 -0.268 0.79571
## Week_23 -1061.5 7151.6 -0.148 0.88567
## Week_24 2263.4 6361.1 0.356 0.73118
## Week_25 -4939.7 5872.9 -0.841 0.42472
## Week_26 1487.9 2184.6 0.681 0.51504
## Week_27 1513.8 7205.9 0.210 0.83886
## Week_28 4954.8 5231.6 0.947 0.37132
## Week_29 1247.1 9404.0 0.133 0.89777
## Week_30 -967.9 6450.5 -0.150 0.88444
## Week_31 9042.4 8957.1 1.010 0.34228
## Week_32 -12285.3 9112.1 -1.348 0.21451
## Week_33 -2887.7 9568.6 -0.302 0.77051
## Week_34 45568.4 16260.1 2.802 0.02311 *
## Week_35 -13289.3 10436.2 -1.273 0.23863
## Week_36 1006.6 10633.8 0.095 0.92691
## Week_37 6034.8 11814.8 0.511 0.62330
## Week_38 1277.1 9477.2 0.135 0.89614
## Week_39 3552.7 8812.1 0.403 0.69739
## Week_40 -7237.7 8644.6 -0.837 0.42675
## Week_41 -8826.3 9972.4 -0.885 0.40194
## Week_42 4938.5 12215.7 0.404 0.69660
## Week_43 -6929.2 11284.7 -0.614 0.55625
## Week_44 3205.8 5255.3 0.610 0.55877
## Week_45 -13801.8 10998.4 -1.255 0.24494
## Week_46 10228.2 11515.2 0.888 0.40033
## Week_47 -6540.1 5890.4 -1.110 0.29913
## Week_48 1976.9 8615.8 0.229 0.82428
## Week_49 5893.4 5511.3 1.069 0.31612
## Week_50 2325.6 5148.6 0.452 0.66348
## Week_51 -4625.2 4880.3 -0.948 0.37102
## Week_52 6727.5 5808.0 1.158 0.28015
## Week_53 -7932.1 5241.0 -1.513 0.16862
## Week_1 1757.7 5383.5 0.327 0.75242
## Week_2 -6339.1 4656.1 -1.361 0.21047
## Week_3 5126.2 6296.8 0.814 0.43915
## Week_4 666.2 7141.2 0.093 0.92797
## Week_5 3683.6 6272.4 0.587 0.57322
## Week_6 -3942.2 4143.7 -0.951 0.36926
## Week_7 2402.7 5507.5 0.436 0.67418
## Week_8 -387.4 6655.4 -0.058 0.95501
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 51290 on 8 degrees of freedom
## Multiple R-squared: 0.897, Adjusted R-squared: 0.215
## F-statistic: 1.315 on 53 and 8 DF, p-value: 0.3613
## [1] "Results for crop: Barley"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -8846.6 -1772.9 321.7 2013.5 5759.6
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 49738.42 12710.79 3.913 0.00446 **
## Week_9 -1003.30 1452.52 -0.691 0.50928
## Week_10 124.56 791.36 0.157 0.87883
## Week_11 35.82 1137.83 0.031 0.97566
## Week_12 172.29 963.41 0.179 0.86251
## Week_13 -1522.91 1548.72 -0.983 0.35424
## Week_14 1770.90 1224.40 1.446 0.18610
## Week_15 284.65 1081.86 0.263 0.79912
## Week_16 607.79 935.02 0.650 0.53389
## Week_17 -467.17 1370.55 -0.341 0.74199
## Week_18 -178.92 879.98 -0.203 0.84396
## Week_19 1051.84 640.36 1.643 0.13909
## Week_20 506.47 1108.45 0.457 0.65988
## Week_21 82.42 910.71 0.091 0.93011
## Week_22 166.19 763.65 0.218 0.83317
## Week_23 -435.58 1013.67 -0.430 0.67875
## Week_24 16.29 901.62 0.018 0.98603
## Week_25 -35.52 832.42 -0.043 0.96701
## Week_26 -134.38 309.65 -0.434 0.67576
## Week_27 876.91 1021.37 0.859 0.41556
## Week_28 -324.57 741.53 -0.438 0.67318
## Week_29 711.46 1332.92 0.534 0.60802
## Week_30 -227.37 914.30 -0.249 0.80987
## Week_31 213.79 1269.57 0.168 0.87045
## Week_32 -120.85 1291.55 -0.094 0.92775
## Week_33 -671.47 1356.26 -0.495 0.63385
## Week_34 4398.79 2304.71 1.909 0.09273 .
## Week_35 -1314.43 1479.22 -0.889 0.40015
## Week_36 43.74 1507.23 0.029 0.97756
## Week_37 505.93 1674.62 0.302 0.77027
## Week_38 716.09 1343.30 0.533 0.60846
## Week_39 -29.42 1249.02 -0.024 0.98179
## Week_40 67.72 1225.28 0.055 0.95728
## Week_41 -825.70 1413.48 -0.584 0.57521
## Week_42 419.10 1731.45 0.242 0.81483
## Week_43 -844.01 1599.50 -0.528 0.61204
## Week_44 290.51 744.89 0.390 0.70671
## Week_45 -1619.67 1558.91 -1.039 0.32920
## Week_46 1131.17 1632.16 0.693 0.50789
## Week_47 -1106.25 834.90 -1.325 0.22176
## Week_48 546.27 1221.20 0.447 0.66651
## Week_49 547.92 781.16 0.701 0.50294
## Week_50 483.32 729.76 0.662 0.52639
## Week_51 -710.68 691.74 -1.027 0.33430
## Week_52 1171.78 823.23 1.423 0.19243
## Week_53 -1221.48 742.86 -1.644 0.13873
## Week_1 581.38 763.05 0.762 0.46797
## Week_2 -1080.40 659.96 -1.637 0.14025
## Week_3 599.55 892.51 0.672 0.52066
## Week_4 28.50 1012.19 0.028 0.97823
## Week_5 325.66 889.04 0.366 0.72364
## Week_6 -226.46 587.33 -0.386 0.70986
## Week_7 -335.21 780.63 -0.429 0.67896
## Week_8 565.28 943.34 0.599 0.56560
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 7269 on 8 degrees of freedom
## Multiple R-squared: 0.8218, Adjusted R-squared: -0.3588
## F-statistic: 0.6961 on 53 and 8 DF, p-value: 0.7967
## [1] "Results for crop: Maize (corn)"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -14959.7 -4658.7 713.5 4478.2 14332.5
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 126972.73 29434.86 4.314 0.00257 **
## Week_9 -1557.14 3363.65 -0.463 0.65575
## Week_10 224.15 1832.58 0.122 0.90567
## Week_11 645.21 2634.91 0.245 0.81272
## Week_12 -78.81 2231.00 -0.035 0.97269
## Week_13 -3897.59 3586.43 -1.087 0.30880
## Week_14 3446.49 2835.39 1.216 0.25882
## Week_15 168.73 2505.30 0.067 0.94796
## Week_16 1973.50 2165.25 0.911 0.38870
## Week_17 625.86 3173.84 0.197 0.84860
## Week_18 -904.07 2037.81 -0.444 0.66905
## Week_19 2173.70 1482.90 1.466 0.18086
## Week_20 804.46 2566.87 0.313 0.76199
## Week_21 83.10 2108.96 0.039 0.96953
## Week_22 -216.91 1768.42 -0.123 0.90540
## Week_23 -399.86 2347.39 -0.170 0.86897
## Week_24 900.39 2087.91 0.431 0.67768
## Week_25 -2017.64 1927.67 -1.047 0.32584
## Week_26 649.74 717.07 0.906 0.39135
## Week_27 1327.77 2365.21 0.561 0.58992
## Week_28 321.44 1717.18 0.187 0.85617
## Week_29 2404.09 3086.70 0.779 0.45848
## Week_30 -885.53 2117.27 -0.418 0.68677
## Week_31 3093.34 2940.00 1.052 0.32347
## Week_32 -2262.99 2990.89 -0.757 0.47096
## Week_33 -558.41 3140.74 -0.178 0.86330
## Week_34 13265.99 5337.10 2.486 0.03778 *
## Week_35 -4490.64 3425.49 -1.311 0.22625
## Week_36 2306.04 3490.35 0.661 0.52737
## Week_37 129.02 3877.98 0.033 0.97427
## Week_38 945.32 3110.73 0.304 0.76896
## Week_39 -172.05 2892.40 -0.059 0.95403
## Week_40 -2550.04 2837.43 -0.899 0.39505
## Week_41 -1216.80 3273.26 -0.372 0.71974
## Week_42 91.34 4009.58 0.023 0.98238
## Week_43 -2321.82 3704.02 -0.627 0.54823
## Week_44 1578.70 1724.96 0.915 0.38684
## Week_45 -4516.59 3610.03 -1.251 0.24624
## Week_46 3623.73 3779.64 0.959 0.36576
## Week_47 -2075.97 1933.42 -1.074 0.31426
## Week_48 209.10 2827.99 0.074 0.94288
## Week_49 1561.89 1808.97 0.863 0.41305
## Week_50 2020.28 1689.92 1.195 0.26613
## Week_51 -2170.75 1601.88 -1.355 0.21240
## Week_52 3126.18 1906.38 1.640 0.13967
## Week_53 -3316.80 1720.26 -1.928 0.08999 .
## Week_1 1061.06 1767.02 0.600 0.56481
## Week_2 -2209.82 1528.29 -1.446 0.18620
## Week_3 1858.65 2066.81 0.899 0.39476
## Week_4 -663.32 2343.97 -0.283 0.78437
## Week_5 921.87 2058.79 0.448 0.66619
## Week_6 -824.92 1360.09 -0.607 0.56098
## Week_7 741.25 1807.73 0.410 0.69253
## Week_8 -444.14 2184.53 -0.203 0.84397
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 16830 on 8 degrees of freedom
## Multiple R-squared: 0.8859, Adjusted R-squared: 0.1301
## F-statistic: 1.172 on 53 and 8 DF, p-value: 0.4389
## [1] "Results for crop: Peaches and nectarines"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -6128.6 -1875.2 -521.9 1580.5 9009.0
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 140722.54 16190.65 8.692 2.39e-05 ***
## Week_9 -997.16 1850.18 -0.539 0.605
## Week_10 -438.30 1008.01 -0.435 0.675
## Week_11 660.67 1449.33 0.456 0.661
## Week_12 -86.30 1227.16 -0.070 0.946
## Week_13 -385.25 1972.72 -0.195 0.850
## Week_14 716.39 1559.61 0.459 0.658
## Week_15 1132.62 1378.04 0.822 0.435
## Week_16 419.10 1191.00 0.352 0.734
## Week_17 -381.99 1745.77 -0.219 0.832
## Week_18 -1140.56 1120.90 -1.018 0.339
## Week_19 494.65 815.67 0.606 0.561
## Week_20 1396.91 1411.91 0.989 0.351
## Week_21 935.94 1160.03 0.807 0.443
## Week_22 -364.02 972.72 -0.374 0.718
## Week_23 -1277.51 1291.18 -0.989 0.351
## Week_24 -33.15 1148.46 -0.029 0.978
## Week_25 225.94 1060.31 0.213 0.837
## Week_26 -650.62 394.42 -1.650 0.138
## Week_27 1667.16 1300.99 1.281 0.236
## Week_28 1037.54 944.54 1.098 0.304
## Week_29 -185.89 1697.84 -0.109 0.916
## Week_30 1064.37 1164.61 0.914 0.387
## Week_31 491.13 1617.15 0.304 0.769
## Week_32 418.15 1645.14 0.254 0.806
## Week_33 -1907.56 1727.56 -1.104 0.302
## Week_34 2609.20 2935.67 0.889 0.400
## Week_35 72.42 1884.19 0.038 0.970
## Week_36 -3211.51 1919.87 -1.673 0.133
## Week_37 397.15 2133.08 0.186 0.857
## Week_38 597.00 1711.06 0.349 0.736
## Week_39 141.02 1590.96 0.089 0.932
## Week_40 184.51 1560.73 0.118 0.909
## Week_41 277.78 1800.46 0.154 0.881
## Week_42 1547.83 2205.47 0.702 0.503
## Week_43 675.11 2037.39 0.331 0.749
## Week_44 -707.76 948.82 -0.746 0.477
## Week_45 -96.43 1985.70 -0.049 0.962
## Week_46 1919.05 2078.99 0.923 0.383
## Week_47 -609.39 1063.48 -0.573 0.582
## Week_48 1835.75 1555.53 1.180 0.272
## Week_49 -862.92 995.02 -0.867 0.411
## Week_50 661.96 929.54 0.712 0.497
## Week_51 165.33 881.11 0.188 0.856
## Week_52 -598.67 1048.61 -0.571 0.584
## Week_53 196.79 946.23 0.208 0.840
## Week_1 944.70 971.95 0.972 0.360
## Week_2 -290.24 840.63 -0.345 0.739
## Week_3 -49.87 1136.85 -0.044 0.966
## Week_4 381.82 1289.30 0.296 0.775
## Week_5 -143.96 1132.44 -0.127 0.902
## Week_6 -552.49 748.12 -0.739 0.481
## Week_7 317.66 994.34 0.319 0.758
## Week_8 202.99 1201.60 0.169 0.870
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 9259 on 8 degrees of freedom
## Multiple R-squared: 0.8753, Adjusted R-squared: 0.04915
## F-statistic: 1.059 on 53 and 8 DF, p-value: 0.5109
## [1] "Results for crop: Wheat"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -6971.8 -1863.0 5.3 2000.5 4963.1
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 42556.40 12179.85 3.494 0.00815 **
## Week_9 -572.41 1391.85 -0.411 0.69168
## Week_10 -24.19 758.30 -0.032 0.97533
## Week_11 -198.47 1090.30 -0.182 0.86009
## Week_12 -36.33 923.17 -0.039 0.96957
## Week_13 -1125.27 1484.03 -0.758 0.47005
## Week_14 1728.84 1173.26 1.474 0.17883
## Week_15 -303.79 1036.67 -0.293 0.77695
## Week_16 806.02 895.96 0.900 0.39459
## Week_17 -910.06 1313.30 -0.693 0.50795
## Week_18 134.93 843.22 0.160 0.87683
## Week_19 848.20 613.61 1.382 0.20424
## Week_20 275.93 1062.15 0.260 0.80159
## Week_21 277.60 872.67 0.318 0.75855
## Week_22 166.16 731.75 0.227 0.82606
## Week_23 -665.94 971.32 -0.686 0.51234
## Week_24 76.91 863.96 0.089 0.93125
## Week_25 -250.94 797.65 -0.315 0.76111
## Week_26 24.80 296.72 0.084 0.93544
## Week_27 602.97 978.70 0.616 0.55496
## Week_28 -312.19 710.55 -0.439 0.67203
## Week_29 430.71 1277.25 0.337 0.74463
## Week_30 -243.22 876.11 -0.278 0.78835
## Week_31 1100.97 1216.54 0.905 0.39190
## Week_32 -137.97 1237.60 -0.111 0.91398
## Week_33 -412.52 1299.61 -0.317 0.75905
## Week_34 4379.28 2208.44 1.983 0.08267 .
## Week_35 -1474.46 1417.43 -1.040 0.32865
## Week_36 315.70 1444.27 0.219 0.83244
## Week_37 165.96 1604.67 0.103 0.92017
## Week_38 442.82 1287.19 0.344 0.73970
## Week_39 -72.83 1196.85 -0.061 0.95297
## Week_40 -645.18 1174.10 -0.550 0.59766
## Week_41 -332.59 1354.44 -0.246 0.81221
## Week_42 1371.37 1659.12 0.827 0.43244
## Week_43 -896.37 1532.68 -0.585 0.57478
## Week_44 285.14 713.77 0.399 0.69999
## Week_45 -1340.21 1493.80 -0.897 0.39582
## Week_46 1491.12 1563.98 0.953 0.36830
## Week_47 -869.81 800.03 -1.087 0.30861
## Week_48 131.67 1170.19 0.113 0.91318
## Week_49 483.78 748.53 0.646 0.53618
## Week_50 392.91 699.27 0.562 0.58959
## Week_51 -579.02 662.84 -0.874 0.40782
## Week_52 1104.11 788.84 1.400 0.19918
## Week_53 -1153.56 711.83 -1.621 0.14377
## Week_1 562.22 731.18 0.769 0.46404
## Week_2 -824.90 632.39 -1.304 0.22837
## Week_3 552.57 855.23 0.646 0.53630
## Week_4 -69.44 969.91 -0.072 0.94468
## Week_5 155.36 851.91 0.182 0.85983
## Week_6 -120.42 562.79 -0.214 0.83593
## Week_7 -471.93 748.02 -0.631 0.54570
## Week_8 539.20 903.94 0.597 0.56733
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 6966 on 8 degrees of freedom
## Multiple R-squared: 0.8461, Adjusted R-squared: -0.1734
## F-statistic: 0.8299 on 53 and 8 DF, p-value: 0.6859
## [1] "Results for crop: Wine"
## [1] "No data available for this crop."
## [1] "Results for crop: Blueberries"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -4605.6 -1360.4 -232.6 1449.1 5309.5
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 38521.875 11000.536 3.502 0.00806 **
## Week_9 647.846 1257.080 0.515 0.62024
## Week_10 -899.902 684.880 -1.314 0.22529
## Week_11 -182.973 984.729 -0.186 0.85722
## Week_12 -1017.470 833.780 -1.220 0.25709
## Week_13 1162.969 1340.338 0.868 0.41085
## Week_14 691.952 1059.656 0.653 0.53207
## Week_15 -362.174 936.293 -0.387 0.70898
## Week_16 718.834 809.209 0.888 0.40029
## Week_17 -857.703 1186.143 -0.723 0.49021
## Week_18 -396.117 761.579 -0.520 0.61706
## Week_19 -157.993 554.196 -0.285 0.78282
## Week_20 555.261 959.304 0.579 0.57864
## Week_21 449.034 788.171 0.570 0.58451
## Week_22 -714.463 660.901 -1.081 0.31119
## Week_23 -66.390 877.276 -0.076 0.94153
## Week_24 -176.164 780.305 -0.226 0.82705
## Week_25 -375.197 720.417 -0.521 0.61661
## Week_26 134.113 267.986 0.500 0.63024
## Week_27 172.668 883.939 0.195 0.85000
## Week_28 132.205 641.753 0.206 0.84193
## Week_29 -903.094 1153.577 -0.783 0.45625
## Week_30 -271.810 791.277 -0.344 0.74007
## Week_31 2488.802 1098.750 2.265 0.05329 .
## Week_32 849.156 1117.768 0.760 0.46923
## Week_33 -150.918 1173.771 -0.129 0.90087
## Week_34 988.691 1994.606 0.496 0.63345
## Week_35 937.116 1280.191 0.732 0.48505
## Week_36 -1666.638 1304.430 -1.278 0.23719
## Week_37 -581.257 1449.298 -0.401 0.69887
## Week_38 -251.693 1162.559 -0.216 0.83402
## Week_39 -1814.209 1080.961 -1.678 0.13180
## Week_40 -133.617 1060.418 -0.126 0.90284
## Week_41 867.682 1223.298 0.709 0.49829
## Week_42 2195.974 1498.479 1.465 0.18096
## Week_43 -267.878 1384.282 -0.194 0.85138
## Week_44 704.986 644.661 1.094 0.30597
## Week_45 -269.031 1349.159 -0.199 0.84692
## Week_46 743.144 1412.546 0.526 0.61309
## Week_47 923.095 722.565 1.278 0.23724
## Week_48 -495.570 1056.889 -0.469 0.65166
## Week_49 -154.610 676.057 -0.229 0.82484
## Week_50 4.261 631.567 0.007 0.99478
## Week_51 77.288 598.662 0.129 0.90046
## Week_52 -88.032 712.463 -0.124 0.90471
## Week_53 105.084 642.904 0.163 0.87422
## Week_1 343.148 660.381 0.520 0.61739
## Week_2 248.877 571.158 0.436 0.67454
## Week_3 -237.961 772.420 -0.308 0.76590
## Week_4 -83.401 875.999 -0.095 0.92649
## Week_5 -691.893 769.421 -0.899 0.39479
## Week_6 434.596 508.300 0.855 0.41742
## Week_7 -469.406 675.593 -0.695 0.50685
## Week_8 275.511 816.413 0.337 0.74445
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 6291 on 8 degrees of freedom
## Multiple R-squared: 0.8683, Adjusted R-squared: -0.00406
## F-statistic: 0.9953 on 53 and 8 DF, p-value: 0.5563
## [1] "Results for crop: Grapes"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -17114.2 -2924.9 -158.6 3303.6 11983.9
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 102045.2 24321.9 4.196 0.00301 **
## Week_9 -2951.6 2779.4 -1.062 0.31926
## Week_10 504.3 1514.3 0.333 0.74765
## Week_11 -461.8 2177.2 -0.212 0.83732
## Week_12 1608.8 1843.5 0.873 0.40826
## Week_13 -5174.7 2963.5 -1.746 0.11893
## Week_14 4605.0 2342.9 1.966 0.08493 .
## Week_15 1154.6 2070.1 0.558 0.59229
## Week_16 1984.7 1789.1 1.109 0.29953
## Week_17 -3014.6 2622.5 -1.150 0.28355
## Week_18 1603.1 1683.8 0.952 0.36893
## Week_19 3047.2 1225.3 2.487 0.03771 *
## Week_20 450.6 2121.0 0.212 0.83706
## Week_21 -1308.3 1742.6 -0.751 0.47430
## Week_22 -180.5 1461.2 -0.124 0.90473
## Week_23 -1035.6 1939.6 -0.534 0.60792
## Week_24 1411.0 1725.2 0.818 0.43711
## Week_25 -1109.2 1592.8 -0.696 0.50591
## Week_26 111.4 592.5 0.188 0.85557
## Week_27 853.8 1954.4 0.437 0.67377
## Week_28 400.7 1418.9 0.282 0.78479
## Week_29 5697.1 2550.5 2.234 0.05597 .
## Week_30 -3374.8 1749.5 -1.929 0.08986 .
## Week_31 -1310.3 2429.3 -0.539 0.60432
## Week_32 180.1 2471.4 0.073 0.94369
## Week_33 -2430.6 2595.2 -0.937 0.37639
## Week_34 9341.6 4410.0 2.118 0.06701 .
## Week_35 -629.7 2830.5 -0.222 0.82951
## Week_36 1093.0 2884.1 0.379 0.71457
## Week_37 526.9 3204.4 0.164 0.87347
## Week_38 2352.0 2570.4 0.915 0.38692
## Week_39 305.2 2390.0 0.128 0.90154
## Week_40 -2235.2 2344.6 -0.953 0.36832
## Week_41 -1094.2 2704.7 -0.405 0.69641
## Week_42 -940.5 3313.1 -0.284 0.78373
## Week_43 -2704.7 3060.6 -0.884 0.40264
## Week_44 1785.3 1425.3 1.253 0.24575
## Week_45 -5830.9 2983.0 -1.955 0.08636 .
## Week_46 3775.0 3123.1 1.209 0.26128
## Week_47 -2768.8 1597.6 -1.733 0.12131
## Week_48 3077.7 2336.8 1.317 0.22428
## Week_49 1504.0 1494.7 1.006 0.34378
## Week_50 1636.8 1396.4 1.172 0.27484
## Week_51 -2625.6 1323.6 -1.984 0.08258 .
## Week_52 4619.1 1575.2 2.932 0.01893 *
## Week_53 -4981.3 1421.4 -3.504 0.00803 **
## Week_1 1332.3 1460.1 0.912 0.38819
## Week_2 -3469.2 1262.8 -2.747 0.02517 *
## Week_3 570.3 1707.8 0.334 0.74701
## Week_4 1625.0 1936.8 0.839 0.42582
## Week_5 584.1 1701.2 0.343 0.74017
## Week_6 -945.8 1123.8 -0.842 0.42448
## Week_7 162.2 1493.7 0.109 0.91622
## Week_8 483.5 1805.1 0.268 0.79558
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 13910 on 8 degrees of freedom
## Multiple R-squared: 0.9061, Adjusted R-squared: 0.2844
## F-statistic: 1.457 on 53 and 8 DF, p-value: 0.2983
## [1] "Results for crop: Raspberries"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -7868.6 -2352.5 -172.8 2045.0 10330.6
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 69498.34 17385.83 3.997 0.00396 **
## Week_9 182.82 1986.76 0.092 0.92894
## Week_10 -488.24 1082.42 -0.451 0.66392
## Week_11 1401.70 1556.32 0.901 0.39408
## Week_12 262.02 1317.75 0.199 0.84735
## Week_13 -3316.72 2118.34 -1.566 0.15605
## Week_14 778.70 1674.74 0.465 0.65435
## Week_15 1359.81 1479.77 0.919 0.38500
## Week_16 -271.98 1278.92 -0.213 0.83691
## Week_17 1749.22 1874.64 0.933 0.37807
## Week_18 -199.49 1203.64 -0.166 0.87247
## Week_19 1593.09 875.88 1.819 0.10644
## Week_20 -580.99 1516.14 -0.383 0.71155
## Week_21 -1201.80 1245.67 -0.965 0.36291
## Week_22 1499.66 1044.52 1.436 0.18900
## Week_23 1536.80 1386.49 1.108 0.29989
## Week_24 -97.31 1233.24 -0.079 0.93905
## Week_25 -431.56 1138.59 -0.379 0.71453
## Week_26 45.93 423.54 0.108 0.91631
## Week_27 354.47 1397.02 0.254 0.80610
## Week_28 384.90 1014.26 0.379 0.71420
## Week_29 1914.92 1823.17 1.050 0.32426
## Week_30 -175.08 1250.58 -0.140 0.89212
## Week_31 -2642.47 1736.52 -1.522 0.16658
## Week_32 -2659.94 1766.58 -1.506 0.17056
## Week_33 -355.73 1855.09 -0.192 0.85271
## Week_34 5987.94 3152.38 1.899 0.09404 .
## Week_35 -5116.09 2023.28 -2.529 0.03533 *
## Week_36 3647.65 2061.59 1.769 0.11480
## Week_37 1307.99 2290.55 0.571 0.58365
## Week_38 1542.16 1837.37 0.839 0.42565
## Week_39 -30.27 1708.41 -0.018 0.98630
## Week_40 -550.55 1675.94 -0.329 0.75097
## Week_41 1229.82 1933.37 0.636 0.54248
## Week_42 -3571.84 2368.28 -1.508 0.16993
## Week_43 1992.44 2187.79 0.911 0.38906
## Week_44 484.27 1018.86 0.475 0.64728
## Week_45 -3217.75 2132.28 -1.509 0.16972
## Week_46 1761.63 2232.46 0.789 0.45280
## Week_47 -259.76 1141.98 -0.227 0.82577
## Week_48 -250.87 1670.36 -0.150 0.88433
## Week_49 1060.20 1068.48 0.992 0.35013
## Week_50 -280.36 998.16 -0.281 0.78593
## Week_51 -999.67 946.16 -1.057 0.32157
## Week_52 970.72 1126.01 0.862 0.41373
## Week_53 -2040.22 1016.08 -2.008 0.07953 .
## Week_1 -87.28 1043.70 -0.084 0.93541
## Week_2 -991.48 902.69 -1.098 0.30400
## Week_3 288.08 1220.77 0.236 0.81938
## Week_4 577.44 1384.47 0.417 0.68759
## Week_5 501.33 1216.03 0.412 0.69097
## Week_6 -537.45 803.34 -0.669 0.52232
## Week_7 888.25 1067.74 0.832 0.42960
## Week_8 -962.18 1290.30 -0.746 0.47719
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 9943 on 8 degrees of freedom
## Multiple R-squared: 0.8581, Adjusted R-squared: -0.08233
## F-statistic: 0.9124 on 53 and 8 DF, p-value: 0.6193
## [1] "Results for crop: Strawberries"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -23747.8 -3986.8 -445.8 4411.7 16525.0
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 125748.66 34010.38 3.697 0.00607 **
## Week_9 -1592.65 3886.52 -0.410 0.69272
## Week_10 -219.32 2117.45 -0.104 0.92005
## Week_11 -20.33 3044.49 -0.007 0.99483
## Week_12 -342.96 2577.80 -0.133 0.89744
## Week_13 -2675.32 4143.93 -0.646 0.53661
## Week_14 2763.37 3276.14 0.843 0.42346
## Week_15 694.49 2894.74 0.240 0.81643
## Week_16 3147.38 2501.83 1.258 0.24386
## Week_17 -1113.40 3667.20 -0.304 0.76917
## Week_18 -571.19 2354.58 -0.243 0.81443
## Week_19 2977.61 1713.41 1.738 0.12044
## Week_20 2108.39 2965.88 0.711 0.49736
## Week_21 -293.62 2436.79 -0.120 0.90706
## Week_22 203.26 2043.31 0.099 0.92321
## Week_23 -1714.36 2712.28 -0.632 0.54497
## Week_24 818.08 2412.47 0.339 0.74326
## Week_25 -1431.45 2227.32 -0.643 0.53841
## Week_26 118.06 828.53 0.142 0.89022
## Week_27 2046.98 2732.88 0.749 0.47529
## Week_28 1387.02 1984.11 0.699 0.50432
## Week_29 2312.19 3566.52 0.648 0.53495
## Week_30 -2410.47 2446.39 -0.985 0.35333
## Week_31 3770.53 3397.01 1.110 0.29926
## Week_32 -770.19 3455.81 -0.223 0.82922
## Week_33 -3133.37 3628.95 -0.863 0.41303
## Week_34 14017.70 6166.73 2.273 0.05263 .
## Week_35 -1243.10 3957.97 -0.314 0.76150
## Week_36 -611.38 4032.91 -0.152 0.88326
## Week_37 49.40 4480.80 0.011 0.99147
## Week_38 1304.50 3594.29 0.363 0.72605
## Week_39 -527.39 3342.01 -0.158 0.87852
## Week_40 -1724.85 3278.50 -0.526 0.61308
## Week_41 -436.42 3782.07 -0.115 0.91098
## Week_42 1175.70 4632.85 0.254 0.80607
## Week_43 -2445.12 4279.79 -0.571 0.58347
## Week_44 1570.02 1993.10 0.788 0.45356
## Week_45 -6939.13 4171.20 -1.664 0.13477
## Week_46 4884.34 4367.17 1.118 0.29584
## Week_47 -1848.76 2233.96 -0.828 0.43190
## Week_48 2050.01 3267.59 0.627 0.54790
## Week_49 1332.17 2090.17 0.637 0.54170
## Week_50 1563.30 1952.62 0.801 0.44648
## Week_51 -1799.93 1850.89 -0.972 0.35930
## Week_52 3067.83 2202.72 1.393 0.20118
## Week_53 -3768.44 1987.67 -1.896 0.09456 .
## Week_1 1766.26 2041.70 0.865 0.41218
## Week_2 -2662.03 1765.85 -1.508 0.17011
## Week_3 1234.90 2388.09 0.517 0.61907
## Week_4 420.36 2708.33 0.155 0.88050
## Week_5 794.93 2378.82 0.334 0.74684
## Week_6 -1354.51 1571.51 -0.862 0.41382
## Week_7 1016.64 2088.73 0.487 0.63951
## Week_8 -737.96 2524.11 -0.292 0.77745
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 19450 on 8 degrees of freedom
## Multiple R-squared: 0.8715, Adjusted R-squared: 0.02028
## F-statistic: 1.024 on 53 and 8 DF, p-value: 0.5357
linear reg for yield VS daily Max Temp
Abbotsford
## [1] "There are 43 NA in the matrix X in Abbotsford station"
## [1] "Results for crop: Apples"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -33286 -15871 64 10493 55755
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -515639.03 318913.35 -1.617 0.1446
## Week_9 -2699.29 7229.07 -0.373 0.7186
## Week_10 662.86 8539.36 0.078 0.9400
## Week_11 -3283.03 11892.83 -0.276 0.7895
## Week_12 13682.96 8156.72 1.678 0.1320
## Week_13 -5296.41 13256.23 -0.400 0.6999
## Week_14 -21007.50 14738.51 -1.425 0.1919
## Week_15 24685.72 11893.14 2.076 0.0716 .
## Week_16 422.03 15611.57 0.027 0.9791
## Week_17 3438.96 14641.66 0.235 0.8202
## Week_18 4679.78 14121.61 0.331 0.7489
## Week_19 6239.70 9835.83 0.634 0.5435
## Week_20 970.91 9538.08 0.102 0.9214
## Week_21 -3476.16 13061.20 -0.266 0.7969
## Week_22 -561.02 8409.07 -0.067 0.9484
## Week_23 -1811.93 7715.60 -0.235 0.8202
## Week_24 -7583.53 8482.87 -0.894 0.3974
## Week_25 -2228.60 8464.18 -0.263 0.7990
## Week_26 9461.88 8506.32 1.112 0.2983
## Week_27 -127.81 16180.24 -0.008 0.9939
## Week_28 6607.71 12773.95 0.517 0.6190
## Week_29 -5452.17 9746.05 -0.559 0.5912
## Week_30 -6857.25 13072.68 -0.525 0.6141
## Week_31 8895.00 10793.52 0.824 0.4338
## Week_32 -3482.08 7606.78 -0.458 0.6593
## Week_33 -4081.18 7804.30 -0.523 0.6152
## Week_34 25782.50 13272.42 1.943 0.0880 .
## Week_35 755.61 8072.85 0.094 0.9277
## Week_36 -4451.57 8823.46 -0.505 0.6275
## Week_37 16769.26 10828.19 1.549 0.1601
## Week_38 3286.65 10453.60 0.314 0.7613
## Week_39 -6308.72 14854.03 -0.425 0.6822
## Week_40 -1882.00 10391.28 -0.181 0.8608
## Week_41 -4544.04 9701.09 -0.468 0.6520
## Week_42 6939.20 9662.43 0.718 0.4931
## Week_43 4836.54 8955.88 0.540 0.6039
## Week_44 -2847.69 6360.79 -0.448 0.6662
## Week_45 -4224.03 17600.02 -0.240 0.8164
## Week_46 4033.82 8835.63 0.457 0.6601
## Week_47 1498.37 4771.24 0.314 0.7615
## Week_48 -5214.67 6060.88 -0.860 0.4146
## Week_49 -6406.70 4160.01 -1.540 0.1621
## Week_50 1345.64 4146.94 0.324 0.7539
## Week_51 -2945.47 4849.56 -0.607 0.5604
## Week_52 166.99 6111.42 0.027 0.9789
## Week_53 -1468.17 4055.60 -0.362 0.7267
## Week_1 2439.59 4661.41 0.523 0.6149
## Week_2 79.32 5724.38 0.014 0.9893
## Week_3 1439.15 5142.70 0.280 0.7867
## Week_4 -5114.54 7575.27 -0.675 0.5186
## Week_5 5698.22 4722.91 1.207 0.2621
## Week_6 -1247.71 5701.82 -0.219 0.8323
## Week_7 4085.42 7141.98 0.572 0.5830
## Week_8 -8259.82 8060.96 -1.025 0.3355
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 53080 on 8 degrees of freedom
## Multiple R-squared: 0.8897, Adjusted R-squared: 0.1591
## F-statistic: 1.218 on 53 and 8 DF, p-value: 0.4124
## [1] "Results for crop: Barley"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -5352.9 -1289.6 44.5 1268.6 5186.5
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -44334.966 38559.454 -1.150 0.2834
## Week_9 58.714 874.059 0.067 0.9481
## Week_10 -759.866 1032.484 -0.736 0.4828
## Week_11 -815.310 1437.949 -0.567 0.5863
## Week_12 1782.095 986.220 1.807 0.1084
## Week_13 -547.485 1602.796 -0.342 0.7415
## Week_14 -1814.796 1782.017 -1.018 0.3383
## Week_15 3325.647 1437.986 2.313 0.0495 *
## Week_16 150.761 1887.577 0.080 0.9383
## Week_17 906.197 1770.306 0.512 0.6226
## Week_18 1059.011 1707.428 0.620 0.5524
## Week_19 1135.631 1189.239 0.955 0.3676
## Week_20 177.984 1153.238 0.154 0.8812
## Week_21 -753.745 1579.215 -0.477 0.6459
## Week_22 444.207 1016.731 0.437 0.6737
## Week_23 -180.859 932.885 -0.194 0.8511
## Week_24 -847.220 1025.654 -0.826 0.4327
## Week_25 -882.623 1023.394 -0.862 0.4135
## Week_26 1021.212 1028.489 0.993 0.3498
## Week_27 318.716 1956.334 0.163 0.8746
## Week_28 -22.215 1544.484 -0.014 0.9889
## Week_29 -979.989 1178.383 -0.832 0.4297
## Week_30 -906.367 1580.603 -0.573 0.5821
## Week_31 696.928 1305.032 0.534 0.6078
## Week_32 402.604 919.727 0.438 0.6732
## Week_33 -327.092 943.609 -0.347 0.7378
## Week_34 2819.259 1604.753 1.757 0.1170
## Week_35 96.135 976.079 0.098 0.9240
## Week_36 -610.709 1066.834 -0.572 0.5827
## Week_37 900.280 1309.224 0.688 0.5111
## Week_38 1341.980 1263.933 1.062 0.3193
## Week_39 -1029.434 1795.984 -0.573 0.5823
## Week_40 -166.678 1256.398 -0.133 0.8977
## Week_41 -359.797 1172.948 -0.307 0.7669
## Week_42 257.680 1168.274 0.221 0.8310
## Week_43 173.944 1082.845 0.161 0.8764
## Week_44 4.258 769.076 0.006 0.9957
## Week_45 -1522.658 2127.999 -0.716 0.4946
## Week_46 892.782 1068.306 0.836 0.4276
## Week_47 6.421 576.885 0.011 0.9914
## Week_48 -920.724 732.814 -1.256 0.2444
## Week_49 -820.255 502.982 -1.631 0.1416
## Week_50 368.577 501.402 0.735 0.4833
## Week_51 -264.215 586.355 -0.451 0.6642
## Week_52 22.269 738.925 0.030 0.9767
## Week_53 -234.739 490.358 -0.479 0.6450
## Week_1 -169.375 563.606 -0.301 0.7714
## Week_2 217.385 692.128 0.314 0.7615
## Week_3 -101.773 621.798 -0.164 0.8740
## Week_4 -244.491 915.918 -0.267 0.7963
## Week_5 233.264 571.042 0.408 0.6936
## Week_6 138.802 689.400 0.201 0.8455
## Week_7 445.329 863.529 0.516 0.6200
## Week_8 -753.527 974.642 -0.773 0.4617
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 6418 on 8 degrees of freedom
## Multiple R-squared: 0.8611, Adjusted R-squared: -0.05905
## F-statistic: 0.9358 on 53 and 8 DF, p-value: 0.601
## [1] "Results for crop: Maize (corn)"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -13144.2 -3118.6 213.3 2357.2 20766.9
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -1.658e+05 9.228e+04 -1.797 0.1101
## Week_9 4.155e+01 2.092e+03 0.020 0.9846
## Week_10 2.752e+02 2.471e+03 0.111 0.9141
## Week_11 -2.697e+03 3.441e+03 -0.784 0.4557
## Week_12 3.838e+03 2.360e+03 1.626 0.1426
## Week_13 1.581e+03 3.836e+03 0.412 0.6910
## Week_14 -6.251e+03 4.265e+03 -1.466 0.1809
## Week_15 5.032e+03 3.441e+03 1.462 0.1818
## Week_16 -1.823e+03 4.517e+03 -0.404 0.6971
## Week_17 -3.512e+02 4.237e+03 -0.083 0.9360
## Week_18 1.651e+03 4.086e+03 0.404 0.6968
## Week_19 1.208e+03 2.846e+03 0.424 0.6825
## Week_20 -3.434e+02 2.760e+03 -0.124 0.9040
## Week_21 -2.656e+02 3.779e+03 -0.070 0.9457
## Week_22 -8.675e+00 2.433e+03 -0.004 0.9972
## Week_23 -5.947e+02 2.232e+03 -0.266 0.7967
## Week_24 -1.048e+03 2.454e+03 -0.427 0.6805
## Week_25 -3.904e+03 2.449e+03 -1.594 0.1496
## Week_26 4.639e+03 2.461e+03 1.885 0.0962 .
## Week_27 -7.126e+02 4.682e+03 -0.152 0.8828
## Week_28 4.893e+03 3.696e+03 1.324 0.2221
## Week_29 -8.304e+02 2.820e+03 -0.294 0.7759
## Week_30 1.064e+03 3.783e+03 0.281 0.7857
## Week_31 2.133e+03 3.123e+03 0.683 0.5139
## Week_32 -3.295e+02 2.201e+03 -0.150 0.8847
## Week_33 -3.800e+02 2.258e+03 -0.168 0.8705
## Week_34 5.948e+03 3.840e+03 1.549 0.1600
## Week_35 -1.161e+03 2.336e+03 -0.497 0.6324
## Week_36 -1.597e+01 2.553e+03 -0.006 0.9952
## Week_37 1.222e+03 3.133e+03 0.390 0.7066
## Week_38 1.341e+03 3.025e+03 0.443 0.6692
## Week_39 -1.100e+03 4.298e+03 -0.256 0.8045
## Week_40 -1.921e+03 3.007e+03 -0.639 0.5407
## Week_41 8.341e+02 2.807e+03 0.297 0.7739
## Week_42 9.599e+02 2.796e+03 0.343 0.7402
## Week_43 -4.337e+02 2.591e+03 -0.167 0.8712
## Week_44 1.356e+03 1.840e+03 0.737 0.4823
## Week_45 1.917e+02 5.092e+03 0.038 0.9709
## Week_46 2.785e+03 2.557e+03 1.089 0.3077
## Week_47 -3.577e+02 1.381e+03 -0.259 0.8021
## Week_48 -5.095e+02 1.754e+03 -0.291 0.7788
## Week_49 -2.460e+03 1.204e+03 -2.044 0.0752 .
## Week_50 6.180e+02 1.200e+03 0.515 0.6204
## Week_51 -3.299e+02 1.403e+03 -0.235 0.8201
## Week_52 -3.944e+01 1.768e+03 -0.022 0.9828
## Week_53 -3.528e+02 1.173e+03 -0.301 0.7713
## Week_1 -4.198e+02 1.349e+03 -0.311 0.7636
## Week_2 -3.267e+02 1.656e+03 -0.197 0.8486
## Week_3 5.732e+01 1.488e+03 0.039 0.9702
## Week_4 1.699e+02 2.192e+03 0.077 0.9401
## Week_5 5.371e+02 1.367e+03 0.393 0.7046
## Week_6 -5.423e+02 1.650e+03 -0.329 0.7508
## Week_7 5.621e+02 2.067e+03 0.272 0.7925
## Week_8 -2.140e+03 2.332e+03 -0.917 0.3857
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 15360 on 8 degrees of freedom
## Multiple R-squared: 0.905, Adjusted R-squared: 0.2759
## F-statistic: 1.439 on 53 and 8 DF, p-value: 0.3059
## [1] "Results for crop: Peaches and nectarines"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -4328.4 -1282.9 -292.3 1570.1 5701.7
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -41717.07 39041.72 -1.069 0.3165
## Week_9 839.19 884.99 0.948 0.3708
## Week_10 -397.20 1045.40 -0.380 0.7139
## Week_11 1193.88 1455.93 0.820 0.4360
## Week_12 1023.88 998.55 1.025 0.3352
## Week_13 1285.67 1622.84 0.792 0.4511
## Week_14 -787.98 1804.30 -0.437 0.6739
## Week_15 938.36 1455.97 0.644 0.5373
## Week_16 -4010.89 1911.18 -2.099 0.0691 .
## Week_17 -1044.38 1792.45 -0.583 0.5762
## Week_18 -3451.28 1728.78 -1.996 0.0810 .
## Week_19 1451.55 1204.11 1.205 0.2625
## Week_20 562.63 1167.66 0.482 0.6428
## Week_21 1832.38 1598.97 1.146 0.2849
## Week_22 482.47 1029.45 0.469 0.6518
## Week_23 1626.79 944.55 1.722 0.1233
## Week_24 -1942.25 1038.48 -1.870 0.0984 .
## Week_25 -310.18 1036.19 -0.299 0.7723
## Week_26 477.32 1041.35 0.458 0.6589
## Week_27 -2770.72 1980.80 -1.399 0.1994
## Week_28 3908.15 1563.80 2.499 0.0370 *
## Week_29 -470.22 1193.12 -0.394 0.7038
## Week_30 2359.89 1600.37 1.475 0.1786
## Week_31 2777.64 1321.35 2.102 0.0687 .
## Week_32 44.05 931.23 0.047 0.9634
## Week_33 -1857.94 955.41 -1.945 0.0877 .
## Week_34 1058.34 1624.82 0.651 0.5331
## Week_35 -106.27 988.29 -0.108 0.9170
## Week_36 -2370.10 1080.18 -2.194 0.0595 .
## Week_37 92.01 1325.60 0.069 0.9464
## Week_38 1403.39 1279.74 1.097 0.3047
## Week_39 1582.06 1818.45 0.870 0.4096
## Week_40 -527.00 1272.11 -0.414 0.6896
## Week_41 1292.02 1187.62 1.088 0.3083
## Week_42 439.40 1182.89 0.371 0.7199
## Week_43 1739.76 1096.39 1.587 0.1512
## Week_44 -797.62 778.69 -1.024 0.3357
## Week_45 3203.05 2154.61 1.487 0.1754
## Week_46 2858.50 1081.67 2.643 0.0296 *
## Week_47 -616.14 584.10 -1.055 0.3223
## Week_48 473.59 741.98 0.638 0.5411
## Week_49 -893.53 509.27 -1.755 0.1174
## Week_50 839.97 507.67 1.655 0.1366
## Week_51 -122.51 593.69 -0.206 0.8417
## Week_52 -225.77 748.17 -0.302 0.7705
## Week_53 321.44 496.49 0.647 0.5355
## Week_1 -327.33 570.65 -0.574 0.5820
## Week_2 -923.15 700.78 -1.317 0.2242
## Week_3 216.77 629.57 0.344 0.7395
## Week_4 702.83 927.37 0.758 0.4703
## Week_5 -233.35 578.18 -0.404 0.6971
## Week_6 -748.88 698.02 -1.073 0.3146
## Week_7 -1822.14 874.33 -2.084 0.0707 .
## Week_8 34.31 986.83 0.035 0.9731
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 6498 on 8 degrees of freedom
## Multiple R-squared: 0.9386, Adjusted R-squared: 0.5317
## F-statistic: 2.307 on 53 and 8 DF, p-value: 0.1044
## [1] "Results for crop: Wheat"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -4802.0 -1403.6 199.2 1119.6 6319.7
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -50474.52 37299.47 -1.353 0.213
## Week_9 192.63 845.50 0.228 0.825
## Week_10 -822.69 998.75 -0.824 0.434
## Week_11 -1955.05 1390.96 -1.406 0.197
## Week_12 1578.64 953.99 1.655 0.137
## Week_13 938.10 1550.42 0.605 0.562
## Week_14 -2395.75 1723.79 -1.390 0.202
## Week_15 2907.22 1391.00 2.090 0.070 .
## Week_16 -342.31 1825.90 -0.187 0.856
## Week_17 1313.88 1712.46 0.767 0.465
## Week_18 2118.79 1651.64 1.283 0.235
## Week_19 470.54 1150.38 0.409 0.693
## Week_20 265.12 1115.55 0.238 0.818
## Week_21 -863.21 1527.61 -0.565 0.588
## Week_22 -20.41 983.51 -0.021 0.984
## Week_23 -302.03 902.40 -0.335 0.746
## Week_24 -963.76 992.14 -0.971 0.360
## Week_25 -1082.20 989.95 -1.093 0.306
## Week_26 823.11 994.88 0.827 0.432
## Week_27 1124.09 1892.41 0.594 0.569
## Week_28 102.34 1494.02 0.069 0.947
## Week_29 -1314.56 1139.88 -1.153 0.282
## Week_30 -704.89 1528.95 -0.461 0.657
## Week_31 1106.09 1262.39 0.876 0.406
## Week_32 175.23 889.67 0.197 0.849
## Week_33 -429.60 912.78 -0.471 0.650
## Week_34 2775.00 1552.32 1.788 0.112
## Week_35 188.63 944.18 0.200 0.847
## Week_36 -498.40 1031.97 -0.483 0.642
## Week_37 532.91 1266.44 0.421 0.685
## Week_38 1130.34 1222.63 0.925 0.382
## Week_39 -1585.68 1737.30 -0.913 0.388
## Week_40 -197.41 1215.34 -0.162 0.875
## Week_41 340.66 1134.62 0.300 0.772
## Week_42 891.02 1130.10 0.788 0.453
## Week_43 672.88 1047.46 0.642 0.539
## Week_44 24.17 743.95 0.032 0.975
## Week_45 -1452.64 2058.46 -0.706 0.500
## Week_46 1574.93 1033.40 1.524 0.166
## Week_47 -216.39 558.03 -0.388 0.708
## Week_48 -561.95 708.87 -0.793 0.451
## Week_49 -790.99 486.55 -1.626 0.143
## Week_50 103.46 485.02 0.213 0.836
## Week_51 -301.43 567.19 -0.531 0.610
## Week_52 -11.83 714.78 -0.017 0.987
## Week_53 -277.62 474.33 -0.585 0.574
## Week_1 48.25 545.19 0.088 0.932
## Week_2 388.26 669.51 0.580 0.578
## Week_3 -475.50 601.48 -0.791 0.452
## Week_4 -354.52 885.99 -0.400 0.700
## Week_5 321.76 552.38 0.582 0.576
## Week_6 -197.01 666.87 -0.295 0.775
## Week_7 448.14 835.31 0.536 0.606
## Week_8 -958.74 942.79 -1.017 0.339
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 6208 on 8 degrees of freedom
## Multiple R-squared: 0.8778, Adjusted R-squared: 0.06796
## F-statistic: 1.084 on 53 and 8 DF, p-value: 0.4944
## [1] "Results for crop: Wine"
## [1] "No data available for this crop."
## [1] "Results for crop: Blueberries"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -5702.7 -1349.4 1.4 1669.4 3881.0
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 7839.85 36258.18 0.216 0.8342
## Week_9 -333.67 821.89 -0.406 0.6954
## Week_10 -1178.51 970.86 -1.214 0.2594
## Week_11 -3590.01 1352.13 -2.655 0.0290 *
## Week_12 1261.74 927.36 1.361 0.2107
## Week_13 2169.08 1507.14 1.439 0.1880
## Week_14 -555.95 1675.66 -0.332 0.7486
## Week_15 535.20 1352.17 0.396 0.7026
## Week_16 960.16 1774.92 0.541 0.6033
## Week_17 2228.02 1664.65 1.338 0.2175
## Week_18 2199.17 1605.53 1.370 0.2080
## Week_19 -325.64 1118.26 -0.291 0.7783
## Week_20 844.90 1084.41 0.779 0.4583
## Week_21 -889.37 1484.97 -0.599 0.5658
## Week_22 -1917.14 956.05 -2.005 0.0799 .
## Week_23 -226.05 877.21 -0.258 0.8031
## Week_24 -97.78 964.44 -0.101 0.9217
## Week_25 -511.91 962.32 -0.532 0.6092
## Week_26 -239.44 967.11 -0.248 0.8107
## Week_27 2769.34 1839.58 1.505 0.1706
## Week_28 421.86 1452.31 0.290 0.7788
## Week_29 -188.05 1108.06 -0.170 0.8695
## Week_30 -1249.50 1486.27 -0.841 0.4249
## Week_31 -36.94 1227.15 -0.030 0.9767
## Week_32 -562.77 864.84 -0.651 0.5335
## Week_33 13.79 887.29 0.016 0.9880
## Week_34 706.33 1508.98 0.468 0.6522
## Week_35 463.58 917.83 0.505 0.6271
## Week_36 140.17 1003.16 0.140 0.8923
## Week_37 -1448.15 1231.09 -1.176 0.2733
## Week_38 1112.12 1188.50 0.936 0.3768
## Week_39 -4316.63 1688.80 -2.556 0.0339 *
## Week_40 965.42 1181.41 0.817 0.4375
## Week_41 1155.50 1102.94 1.048 0.3254
## Week_42 1907.43 1098.55 1.736 0.1207
## Week_43 1104.76 1018.22 1.085 0.3095
## Week_44 591.90 723.18 0.818 0.4368
## Week_45 -3018.99 2001.00 -1.509 0.1698
## Week_46 1702.88 1004.55 1.695 0.1285
## Week_47 437.14 542.46 0.806 0.4436
## Week_48 62.91 689.08 0.091 0.9295
## Week_49 -86.33 472.96 -0.183 0.8597
## Week_50 -659.45 471.48 -1.399 0.1995
## Week_51 -430.40 551.36 -0.781 0.4575
## Week_52 -77.63 694.82 -0.112 0.9138
## Week_53 -250.63 461.09 -0.544 0.6016
## Week_1 120.19 529.97 0.227 0.8263
## Week_2 815.66 650.82 1.253 0.2455
## Week_3 -465.18 584.69 -0.796 0.4492
## Week_4 19.45 861.25 0.023 0.9825
## Week_5 -664.70 536.96 -1.238 0.2509
## Week_6 -192.77 648.26 -0.297 0.7738
## Week_7 633.04 811.99 0.780 0.4581
## Week_8 -728.60 916.47 -0.795 0.4496
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 6035 on 8 degrees of freedom
## Multiple R-squared: 0.8788, Adjusted R-squared: 0.07615
## F-statistic: 1.095 on 53 and 8 DF, p-value: 0.4872
## [1] "Results for crop: Grapes"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -12448.7 -3502.3 193.7 3786.4 13234.4
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 112133.30 80399.57 1.395 0.20061
## Week_9 -2793.84 1822.48 -1.533 0.16382
## Week_10 -2351.08 2152.81 -1.092 0.30658
## Week_11 -4337.65 2998.24 -1.447 0.18599
## Week_12 2048.41 2056.35 0.996 0.34835
## Week_13 -2532.43 3341.96 -0.758 0.47032
## Week_14 -4707.17 3715.65 -1.267 0.24084
## Week_15 11230.72 2998.32 3.746 0.00566 **
## Week_16 9815.58 3935.75 2.494 0.03729 *
## Week_17 9466.78 3691.23 2.565 0.03340 *
## Week_18 7928.27 3560.13 2.227 0.05656 .
## Week_19 -1128.59 2479.66 -0.455 0.66111
## Week_20 856.61 2404.60 0.356 0.73087
## Week_21 -7926.60 3292.79 -2.407 0.04269 *
## Week_22 -253.20 2119.97 -0.119 0.90787
## Week_23 -4197.76 1945.14 -2.158 0.06298 .
## Week_24 -1847.94 2138.57 -0.864 0.41269
## Week_25 -1731.49 2133.86 -0.811 0.44059
## Week_26 1874.95 2144.48 0.874 0.40743
## Week_27 6735.39 4079.11 1.651 0.13731
## Week_28 -3863.43 3220.37 -1.200 0.26458
## Week_29 1611.31 2457.02 0.656 0.53036
## Week_30 -7912.49 3295.68 -2.401 0.04312 *
## Week_31 -2952.77 2721.10 -1.085 0.30947
## Week_32 -673.64 1917.71 -0.351 0.73445
## Week_33 228.80 1967.50 0.116 0.91029
## Week_34 3408.61 3346.04 1.019 0.33816
## Week_35 4223.16 2035.20 2.075 0.07166 .
## Week_36 2930.23 2224.44 1.317 0.22422
## Week_37 663.77 2729.84 0.243 0.81400
## Week_38 3236.61 2635.40 1.228 0.25430
## Week_39 -10232.13 3744.77 -2.732 0.02575 *
## Week_40 1769.04 2619.69 0.675 0.51853
## Week_41 -3185.95 2445.69 -1.303 0.22893
## Week_42 -450.06 2435.94 -0.185 0.85802
## Week_43 -672.24 2257.82 -0.298 0.77349
## Week_44 -932.16 1603.59 -0.581 0.57705
## Week_45 -11598.72 4437.05 -2.614 0.03093 *
## Week_46 2073.12 2227.50 0.931 0.37924
## Week_47 1072.76 1202.85 0.892 0.39851
## Week_48 -2547.14 1527.98 -1.667 0.13407
## Week_49 -43.11 1048.76 -0.041 0.96822
## Week_50 339.86 1045.46 0.325 0.75346
## Week_51 -2059.93 1222.60 -1.685 0.13050
## Week_52 1596.31 1540.72 1.036 0.33046
## Week_53 -1967.42 1022.44 -1.924 0.09052 .
## Week_1 666.10 1175.16 0.567 0.58639
## Week_2 2095.77 1443.14 1.452 0.18450
## Week_3 2129.65 1296.50 1.643 0.13909
## Week_4 -4412.18 1909.76 -2.310 0.04966 *
## Week_5 964.84 1190.67 0.810 0.44119
## Week_6 1711.69 1437.45 1.191 0.26787
## Week_7 4290.38 1800.53 2.383 0.04435 *
## Week_8 -4679.71 2032.21 -2.303 0.05025 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 13380 on 8 degrees of freedom
## Multiple R-squared: 0.9131, Adjusted R-squared: 0.3377
## F-statistic: 1.587 on 53 and 8 DF, p-value: 0.2513
## [1] "Results for crop: Raspberries"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -8245.9 -2322.8 58.6 2340.2 9916.1
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -20164.05 57522.31 -0.351 0.735
## Week_9 -1077.69 1303.91 -0.827 0.432
## Week_10 1056.12 1540.24 0.686 0.512
## Week_11 650.51 2145.11 0.303 0.769
## Week_12 253.29 1471.23 0.172 0.868
## Week_13 -3572.28 2391.02 -1.494 0.174
## Week_14 760.92 2658.38 0.286 0.782
## Week_15 3945.94 2145.16 1.839 0.103
## Week_16 3105.62 2815.85 1.103 0.302
## Week_17 -189.49 2640.91 -0.072 0.945
## Week_18 -145.33 2547.11 -0.057 0.956
## Week_19 697.69 1774.09 0.393 0.704
## Week_20 -1048.36 1720.38 -0.609 0.559
## Week_21 767.26 2355.84 0.326 0.753
## Week_22 2097.25 1516.74 1.383 0.204
## Week_23 -960.54 1391.66 -0.690 0.510
## Week_24 1240.71 1530.05 0.811 0.441
## Week_25 -70.60 1526.68 -0.046 0.964
## Week_26 1171.28 1534.28 0.763 0.467
## Week_27 -586.00 2918.42 -0.201 0.846
## Week_28 -1486.37 2304.03 -0.645 0.537
## Week_29 1114.77 1757.89 0.634 0.544
## Week_30 -1533.22 2357.92 -0.650 0.534
## Week_31 -578.17 1946.82 -0.297 0.774
## Week_32 1012.67 1372.03 0.738 0.482
## Week_33 -1083.45 1407.66 -0.770 0.464
## Week_34 1372.22 2393.94 0.573 0.582
## Week_35 -767.41 1456.10 -0.527 0.612
## Week_36 1072.17 1591.48 0.674 0.519
## Week_37 3598.08 1953.08 1.842 0.103
## Week_38 -1051.10 1885.51 -0.557 0.592
## Week_39 435.99 2679.22 0.163 0.875
## Week_40 -306.03 1874.27 -0.163 0.874
## Week_41 -1737.74 1749.78 -0.993 0.350
## Week_42 -1425.30 1742.81 -0.818 0.437
## Week_43 -1388.64 1615.37 -0.860 0.415
## Week_44 472.81 1147.29 0.412 0.691
## Week_45 -1791.41 3174.51 -0.564 0.588
## Week_46 -1907.65 1593.68 -1.197 0.266
## Week_47 851.79 860.59 0.990 0.351
## Week_48 -1133.27 1093.20 -1.037 0.330
## Week_49 -454.77 750.34 -0.606 0.561
## Week_50 225.69 747.98 0.302 0.771
## Week_51 -1081.94 874.71 -1.237 0.251
## Week_52 1382.83 1102.31 1.254 0.245
## Week_53 -711.16 731.51 -0.972 0.359
## Week_1 -305.22 840.78 -0.363 0.726
## Week_2 1226.81 1032.50 1.188 0.269
## Week_3 12.91 927.59 0.014 0.989
## Week_4 -38.37 1366.35 -0.028 0.978
## Week_5 325.63 851.87 0.382 0.712
## Week_6 247.79 1028.43 0.241 0.816
## Week_7 1885.25 1288.20 1.463 0.181
## Week_8 -603.88 1453.95 -0.415 0.689
##
## Residual standard error: 9574 on 8 degrees of freedom
## Multiple R-squared: 0.8684, Adjusted R-squared: -0.003459
## F-statistic: 0.996 on 53 and 8 DF, p-value: 0.5558
## [1] "Results for crop: Strawberries"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -9605.5 -3589.4 -453.4 3413.7 13219.0
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -117130.74 84447.31 -1.387 0.2029
## Week_9 -1358.47 1914.24 -0.710 0.4981
## Week_10 -1332.42 2261.20 -0.589 0.5720
## Week_11 -4123.16 3149.19 -1.309 0.2268
## Week_12 3031.39 2159.88 1.404 0.1981
## Week_13 1393.36 3510.21 0.397 0.7018
## Week_14 -6796.86 3902.71 -1.742 0.1198
## Week_15 7772.94 3149.27 2.468 0.0388 *
## Week_16 3218.83 4133.90 0.779 0.4586
## Week_17 4831.33 3877.07 1.246 0.2480
## Week_18 3897.67 3739.36 1.042 0.3277
## Week_19 614.63 2604.50 0.236 0.8194
## Week_20 1844.77 2525.66 0.730 0.4860
## Week_21 -4366.74 3458.57 -1.263 0.2423
## Week_22 -808.69 2226.70 -0.363 0.7259
## Week_23 -1902.70 2043.07 -0.931 0.3789
## Week_24 -1976.95 2246.24 -0.880 0.4045
## Week_25 -2340.67 2241.29 -1.044 0.3269
## Week_26 3866.26 2252.45 1.716 0.1244
## Week_27 1853.72 4284.48 0.433 0.6767
## Week_28 2568.20 3382.50 0.759 0.4695
## Week_29 -689.31 2580.72 -0.267 0.7961
## Week_30 -4137.12 3461.61 -1.195 0.2663
## Week_31 2183.53 2858.09 0.764 0.4668
## Week_32 -626.12 2014.25 -0.311 0.7639
## Week_33 -1642.49 2066.56 -0.795 0.4497
## Week_34 5709.57 3514.50 1.625 0.1429
## Week_35 2503.00 2137.67 1.171 0.2753
## Week_36 -19.91 2336.43 -0.009 0.9934
## Week_37 1057.13 2867.27 0.369 0.7219
## Week_38 1709.18 2768.08 0.617 0.5541
## Week_39 -5569.75 3933.30 -1.416 0.1945
## Week_40 1667.97 2751.58 0.606 0.5612
## Week_41 -685.59 2568.82 -0.267 0.7963
## Week_42 1152.67 2558.58 0.451 0.6643
## Week_43 1132.52 2371.49 0.478 0.6457
## Week_44 544.74 1684.32 0.323 0.7547
## Week_45 -5784.71 4660.43 -1.241 0.2497
## Week_46 3999.55 2339.65 1.709 0.1257
## Week_47 828.02 1263.41 0.655 0.5306
## Week_48 -1276.81 1604.90 -0.796 0.4492
## Week_49 -1641.10 1101.56 -1.490 0.1746
## Week_50 165.23 1098.10 0.150 0.8841
## Week_51 -1140.50 1284.15 -0.888 0.4004
## Week_52 610.44 1618.29 0.377 0.7158
## Week_53 -950.05 1073.91 -0.885 0.4021
## Week_1 430.45 1234.33 0.349 0.7363
## Week_2 432.32 1515.80 0.285 0.7827
## Week_3 1246.78 1361.77 0.916 0.3867
## Week_4 -2026.16 2005.91 -1.010 0.3420
## Week_5 571.82 1250.61 0.457 0.6597
## Week_6 166.74 1509.82 0.110 0.9148
## Week_7 1629.22 1891.18 0.861 0.4140
## Week_8 -4098.43 2134.52 -1.920 0.0911 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 14060 on 8 degrees of freedom
## Multiple R-squared: 0.9329, Adjusted R-squared: 0.4884
## F-statistic: 2.099 on 53 and 8 DF, p-value: 0.1326
